1. Field of the Invention
The present invention relates, in general, to sensor fusion and, more particularly, to sensor fusion in medical devices incorporating multiple monitors of multiple patient parameters.
2. Description of the Related Art
Spurious monitored data may cause systems that rely on them to take potentially hazardous action, to fail to take action in critical situations, or to alarm unnecessarily. For example, a sedation and analgesia system may be monitoring a patient's heart rate with an electrocardiograph (ECG) when the ECG becomes erratic. Based on the single monitor, the sedation and analgesia system may signal an alarm indicating, for example, a dangerously low heart rate, when the erratic ECG data is actually spurious. A high frequency of these false positive alarms may annoy clinicians and may result in less attention being given to truly life-threatening conditions.
Sensor fusion is herein defined as the analysis of monitored data and information from at least one sensor, given a first patient parameter, along with data from at least one other sensor, given a second patient parameter, in order to increase the sensitivity and specificity of parameters defining a patient state. A highly sensitive system ensures that system ensures that when a truly critical event occurs, that event is not missed. In a highly specific system, when an alarm does sound, the alarm is representative of a truly critical situation and is not based on spurious data. Providing a single monitor, such as an ECG, to monitor heart rate may result in a sedation and analgesia system having a low specificity where, for example, a clinician's motion in the surgical field can add disruptive electrical activity that the ECG may interpret as ventricular fibrillation. Without any means of verifying the data presented by the ECG, the monitor would alarm to alert the attending clinician of a potentially life threatening situation even though the data may be spurious.
Monitoring problems may also arise when monitors such as, for example, capnometers, provide inconclusive evidence regarding patient condition. Air brought into the lungs during inhalation typically carries a negligible amount of carbon dioxide due to the nominal concentration of the gas in the atmosphere. As atmospheric air passes into the lungs it will participate in gas transfer across alveolar membranes, where oxygen is taken into the blood and carbon dioxide is excreted for removal from the body. The eliminated carbon dioxide is commonly used by capnometers to ascertain a patient's respiratory rate, to determine whether they are experiencing sufficient gas exchange, and for other ventilatory reasons. When monitored with capnometry, a healthy patient breathing normally will produce a capnogram with a series of waveforms. The peak of each waveform is known as the end-tidal carbon dioxide (EtCO2) level. The peak at the end of each exhalation is generally most representative of the gas exchange occurring at the alveolar level where gases expired at the end of exhalation have been held for the longest portion of time in the deepest portions of the lungs where alveolar gas exchange takes place. Thus, end-tidal carbon dioxide is clinically interpreted as representing the patient's blood level of carbon dioxide, the trend of which reflects the patient's ventilatory state over time.
During inhalation, a nominal capnometry waveform can then generally be seen as a period of negligible carbon dioxide during inhalation (due to the low atmospheric gas concentration) followed by a second period of negligible carbon dioxide during the beginning of exhalation (where gas is expelled from upper regions of the respiratory tract that do not participate in gas exchange). Following inhalation and the beginning of exhalation, the waveform indicating carbon dioxide levels will rise sharply before beginning to plateau and finally peaking at the end of exhalation at the EtCO2. Following exhalation, the carbon dioxide levels will drop sharply to a negligible level as inhalation begins once again.
Though capnometers are commonly used and are useful in ascertaining the above-mentioned patient parameters, it may be difficult to differentiate, using only capnometry, between hyperventilation (often a non-critical issue) and hypoventilation (a highly critical and potentially life-threatening condition.) Hyperventilation is generally characterized by shallow, fast, short breaths, where capnometers will show a dramatic decrease in expired carbon dioxide as the patient's hyperventilatory state serves to deplete the blood stores of carbon dioxide.
Hypoventilation is generally characterized by depressed respiration, where hypoventilation may be caused by, for example, drug overdose and airway obstruction. Although the underlying patient physiology is entirely different in hypoventilation compared to hyperventilation, the condition can look surprisingly similar to a capnometer. Like hyperventilation, hypoventilation caused by partial or complete airway obstruction will often also register as a series of diminished capnography waveforms and a low level of end-tidal carbon dioxide. In the case of hypoventilation, the diminished capnography waveforms are caused by inadequate exhalation of air past the airway obstruction. Since the capnometry waveforms of both hyperventilation and hypoventilation patient states can appear very similar, when monitoring is done solely by capnometry, there is no choice in monitoring algorithms but to alarm in either patient state in order to avoid potentially missing a life-threatening hypoventilation event. However, such a system may also result in frequent false positive alarms based on the benign condition of hyperventilation.
Though patient parameters such as heart rate, capnometry, pulse oximetry, blood pressure, and others are generally monitored separately when determining patient condition, such parameters often have underlying physiological dependencies and correlations that allow for information about one to be gathered by monitoring another. For example, heart rate as monitored by an electrocardiograph (ECG) is physiologically related to pulse oximetry monitoring. The electrical activation of the ventricles illustrates the major waveform (QRS) detected on the ECG, in a one-to-one ratio with the plethysmogram, representing a pulsatile wave of blood motion under the pulse oximeter's monitored site. When the two waveforms are compared, the QRS portion of the ECG generally occurs a few milliseconds before a pulse in the plethysmogram waveform. If a severe disruption of cardiac output occurs, such as that associated with ventricular fibrillation, the plethysmogram will no longer correlate one-to-one with the ECG and will be irregular. Therefore, if an ECG reading indicates that a potentially life-threatening patient event is occurring, the plethysmogram will likely also indicate such a negative event. If the information from these two disparate monitors is processed together, the output can significantly increase the specificity of alarm algorithms. Furthermore, if the ECG becomes erratic due to, for example, clinician motion in the surgical field, the plethysmogram will likely remain regular, whereupon it may be inferred that the irregular ECG is spurious and not the result of a truly life-threatening patient event.
Often, there are patient parameters that are difficult to measure due to their invasiveness into the human body, yet may serve as beneficial indicators of a patient's condition. For example, systemic vascular resistance (SVR), if measured directly, may require the insertion of an uncomfortable monitoring device into the patient's blood vessels. Such an invasive procedure may preclude clinicians from using such a monitoring device, where potentially important information related to a patient's cardiovascular or hemodynamic condition will go unmonitored.